MAJIS instrument thermal model correlation using flight data

Thermal control represents a fundamental aspect for the correct operation of space instruments, particularly in the case of interplanetary missions characterized by complex thermal environments. In this context, the capability of thermal models to accurately reproduce the real behaviour of the system is essential to ensure the reliability of operational predictions. This work addresses the optimization and validation of the thermal model of the MAJIS instrument (Moons and Jupiter Imaging Spectrometer), onboard the JUICE mission of the European Space Agency (ESA), using telemetry data acquired in flight during the cruise phase. The correlation of the thermal model with flight data represents a fundamental step to improve its accuracy and predictive capability. In a first phase, an analysis of the discrepancies between the temperatures simulated by the Thermal Mathematical Model (TMM) and the measured data was carried out, both under steady-state conditions and in transient regime, in order to identify the main sources of error and the associated parameters. Subsequently, a parameter optimization methodology based on Design of Experiments (DOE) techniques was developed, with particular reference to the Latin Hypercube Sampling (LHS) method, enabling a systematic exploration of the uncertain parameter space. The optimization process led to a significant reduction of the error between the model and the flight data under steady-state conditions, reducing the RMSE from values around 5$^\circ$C to values below 3$^\circ$C. However, the analysis of the results highlights that some discrepancies still persist, indicating that the thermal response of the subsystems is not fully captured by the current model parameterization. The validation of the correlated model through an independent transient case confirmed the capability of the model to qualitatively reproduce the system dynamics, while highlighting limitations in the representation of the temporal response. These results suggest that the remaining discrepancies are not primarily attributable to parameter uncertainty, but rather to structural limitations and assumptions of the adopted modelling approach. The work carried out provides a structured framework for the correlation of thermal models using in-flight data, contributing to the improvement of model reliability and being applicable to other space instruments characterized by similar thermal constraints.